Data Science Program

About Course

Course Overview:

This course is designed to provide you with a comprehensive introduction to data science, machine learning, artificial intelligence, deep learning, and data visualization. You will gain practical knowledge of Python, SQL, and various data science techniques to solve real-world problems.

Course Duration:

The course is designed to be completed in approximately 4 to 6 months, depending on your pace.
It consists of 6 main modules, each with practical exercises and projects.

What Will You Learn?

Data Science Basics: Understand core data science concepts and the importance of Python.
Machine Learning: Learn supervised and unsupervised learning methods.
Artificial Intelligence: Get an introduction to AI, including neural networks and logical reasoning.
Deep Learning: Master deep learning algorithms for complex problem-solving.
Data Visualization: Learn to create insightful and interactive visualizations with Tableau.
SQL for Data Management: Develop skills to work with relational databases using SQL.

Material Includes

Python programming resources.
Access to tools like Jupyter Notebook, PyCharm, and Tableau.
Real-world datasets for practice.
Hands-on projects to apply knowledge.
Reading materials and references to key topics.

Course Curriculum

Module 1: Introduction to Data Science

Overview of Data Science, key concepts, and applications in industries.

Module 2: Introduction to Python

Module 3: Python Basics

Module 4: Python Packages

Module 5: Importing Data

Module 6: Manipulating Data

Module 7: Statistics Basics

Module 8: Error Metrics

Module 9: Machine Learning

Module 10: Artificial Intelligence (AI)

Module 11: Deep Learning

Module 12: Data Visualization with Tableau

Module 13: SQL for Data Management

Your Instructors

kodestree

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Data Science Program

March 1, 2025

About Course

What Will You Learn?

Material Includes

Course Curriculum

Module 1: Introduction to Data Science

Overview of Data Science, key concepts, and applications in industries.

Module 2: Introduction to Python

Python setup, syntax, data types, and working with basic constructs.

Module 3: Python Basics

Explore data structures, functions, and file handling in Python.

Module 4: Python Packages

Introduction to libraries like NumPy, Pandas, Matplotlib, and Scikit-learn.

Module 5: Importing Data

Learn to read and manipulate data using Pandas from various sources.

Module 6: Manipulating Data

Data transformation and cleaning techniques, handling missing values.

Module 7: Statistics Basics

Learn key statistical concepts like mean, variance, distributions, and hypothesis testing.

Module 8: Error Metrics

Understand classification and regression error metrics to evaluate model performance.

Module 9: Machine Learning

Explore supervised and unsupervised learning algorithms such as linear regression, SVM, and K-means.

Module 10: Artificial Intelligence (AI)

Dive into the fundamentals of AI, logical reasoning, and problem-solving.

Module 11: Deep Learning

Learn deep learning algorithms like CNNs, RNNs, and how they are applied to various data types.

Module 12: Data Visualization with Tableau

Learn to create and publish interactive dashboards and reports using Tableau.

Module 13: SQL for Data Management

Master SQL queries, data manipulation, and working with relational databases.

Your Instructors

kodestree

This course includes:

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